Wednesday, August 5, 2026

AI Involves Lots of Politicial Choices: For Whom and Why

It’s easy enough to argue that widespread use of artificial intelligence has some potential to raise important new questions about economic life, political choices and values. 


“The question is not which jobs will survive. It is what kind of economy we are building, and for whom,” a World Economic Forum note asks. 


“A livelihood is not a role,” WEF suggests. “ It is a sustained capacity to generate value, dignity and security over time, for a person, their family and their society.”


“It encompasses income, but also purpose, identity and belonging,” WEF notes.


Catholic social teaching dovetails. 


Catholic social teaching assigns work an importance that goes well beyond economics or material production. 


Principle

Meaning

Representative documents

Work has inherent dignity

Human work possesses value beyond wages or productivity because workers are made in God's image.

Rerum Novarum, Laborem Exercens

The worker is more important than the work

Persons must never be treated merely as instruments of production.

Laborem Exercens

Work participates in creation

Human labor continues God's creative work by cultivating and improving creation.

Gaudium et Spes, Laborem Exercens

Work contributes to human flourishing

Work develops talents, virtues, responsibility, and community.

Gaudium et Spes

Work serves the common good

Labor should benefit families, society, and future generations.

Centesimus Annus, Caritas in Veritate

Economic systems exist for persons

Markets are valuable but must remain ordered toward human dignity rather than treating labor as merely another input.

Rerum Novarum, Quadragesimo Anno, Centesimus Annus


Work is not simply a means of earning income, nor is it merely a commodity bought and sold in markets. 


Instead, work is understood as an essential aspect of human dignity, a way in which persons participate in God's continuing work of creation, develop their own humanity, serve their neighbors, and contribute to the common good.


So AI has spiritual and religious implications.


John Paul II explained that because humans are created in God's image, they imitate God's own creative activity through their labor. 


Perhaps the most distinctive contribution of the encyclical Laborem Exercens is its teaching that work is participation in creation.


For such reasons, even some apparently-appealing ideas such as universal basic income are insufficient compensation for AI-induced productivity gains. 


Work matters for human dignity and meaning, and UBI does not help, in that regard. 


Humans need “work” because, as the Second Vatican Council's Gaudium et Spes teaches:

  • through work people develop their talents;

  • acquire virtues;

  • grow in responsibility;

  • contribute to society;

  • become more fully themselves.


Gaudium et Spes marked the first time an ecumenical council addressed the entire world rather than just focusing on internal church matters. It established modern Catholic social teaching, so is foundational. 


Catholic social teaching is that work is fundamentally relational and imbued with moral purpose.


Work serves:

  • one's family

  • customers

  • fellow workers

  • local communities

  • society as a whole.


Markets help coordinate work, but the moral purpose of work extends beyond markets, as markets and work are ordered to the promotion of the common good of society and people, including:

  • economic prosperity

  • cultural development

  • scientific advancement

  • political stability

  • social solidarity. 


So employment and work are viewed not merely as a private contract but as participation in building society.


For that reason, pursuit of the common good means supporting:

  • opportunities for productive employment

  • just wages

  • safe working conditions

  • reasonable working hours

  • rights of association and labor unions

  • protection of family life.


Catholic social teaching suggests several enduring principles:

  • Economic systems exist for persons, not persons for economic systems

  • Every form of honest work possesses inherent dignity

  • Workers should never be reduced to costs or commodities

  • Technological innovation should enhance rather than diminish human flourishing

  • Work is both economically productive and spiritually formative

  • Human labor contributes to God's continuing work of creation and to the common good.


AI does raise these issues in a new context. How do we ensure humans have work, irrespective of the impact of AI? 


Because work matters, not simply as a means to sustenance, but as a fundamental expression of human creativity. 


At the same time, Catholic social teaching disagrees with purely market-based views (which reduce work to a commodity) and purely collectivist views (which subordinate the worker to the state). 


“Markets that operate with morals” might be one somewhat inadequate way of expressing the formulation. 


Tuesday, August 4, 2026

Off-Balance-Sheet Financing is an Infrastructure Staple

The AI infrastructure boom has changed the nature of hyperscaler financial commitments. Traditionally, investors focused on on-balance-sheet debt (bonds, bank loans and finance leases). Today, a growing issue is contractual obligations that are legally binding but are not yet recognized as liabilities under U.S. generally accepted accounting practices.


These commitments include:

  • Multi-decade data center leases

  • Colocation agreements

  • GPU purchase commitments

  • Power purchase agreements (PPAs)

  • Network infrastructure contracts

  • Joint venture funding commitments

  • Capacity reservation agreements


The accounting treatment, while legitimate, represents future fixed cash commitments not reflected on balance sheets. 


According to Moody's Ratings, at year-end 2025, about $1.9 trillion in such future commitments were incumbent on a few hyperscale high-performance-computing suppliers::

Item

Amount

Total undiscounted future data center lease commitments

$969 billion

Not yet commenced (therefore largely off balance sheet)

$662 billion

Portion already commenced

about $307 billion


According to Moody's, $662 billion of uncommenced lease obligations exceeded the group's adjusted reported debt by roughly 113 percent. 


Company

Major off-balance-sheet commitments

Approximate current scale (2026)

Likely growth through 2028

Alphabet

AI data center leases, TPU infrastructure, power contracts

roughly $120B-$170B

$200B+ possible

Amazon

Data center leases, AWS capacity, equipment commitments

roughly $180B-$250B

$300B-$400B possible

Microsoft

Azure leases, OpenAI infrastructure, private investment funds

roughly $150B-$220B

$250B-$350B possible

Meta Platforms

AI campuses, Hyperion leases, networking

about $279B disclosed lease commitments after Q2; additional July commitments announced

$350B-$450B possible

Oracle

OCI data centers, GPU commitOfments, leased facilities

roughly $50B-$100B

$100B-$150B possible


Meta provides one of the clearest examples:

  • future AI lease obligations appr;;;;;;\\q12aaching $279 billion

  • another approximately $68 billion of new leases signed after quarter-end

  • lease terms extending as long as 30 years

  • commitments tied to multiple multi-gigawatt AI campuses.


Many obligations never appear as debt but nevertheless commit future cash flow:

Commitment type

Typical accounting treatment

Economic effect

Long-term data center leases

Recognized when lease commences

Future fixed payments

GPU purchase contracts

Usually not recognized until delivery

Locked capital spending

Power purchase agreements

Often disclosed as commitments

Long-term electricity costs

Network capacity reservations

Footnote disclosure

Fixed operating expense

Joint venture funding

Often partially off balance sheet

Future capital contributions

Colocation agreements

Lease recognition delayed until commencement

Multi-year cash obligations


Such practices are common in other capital intensive industries, or parts of industry infrastructure, including airline transportation providers, because doing so:

  • preserves reported leverage ratios

  • matches accounting recognition to asset availability

  • allows capacity to be secured years before facilities open

  • enables landlords and infrastructure funds to finance construction

  • reduces the need to issue corporate debt immediately. 


If AI capital spending continues near today's pace, a reasonable scenario for Alphabet, Amazon, Microsoft, Meta and Oracle is:

p[;;;;;

Year

Estimated aggregate off-balance-sheet commitments (five hyperscalers)

2025

~$662B (Moody's estimate of uncommenced leases)

2026

~$800B-$1.0T

2027

~$1.1T-$1.4T

2028

~$1.3T-$1.7T


The issue for some observers is whether such future commitments are a problem, or not. Even if not considered “debt” in a GAAP sense:

  • They require future cash payments.

  • They reduce future financial flexibility.

  • Many cannot easily be canceled without substantial penalties.

  • Credit analysts increasingly incorporate them into leverage analysis.


The issue is impact on firm leverage


But that seemingly often is an issue with the financing of infrastructure. Railroads, electric utilities, pipelines, airports, seaports, cellular networks, and fiber networks all required enormous up-front investment years before meaningful revenues arrived. 


Each wave developed financing techniques that shifted risk away from the sponsoring company while securing long-term capital.


Infrastructure era

Typical financing

Off-balance-sheet elements

Primary revenue support

Similarity to AI infrastructure

Railroads (1800s)

Corporate bonds, land grants

Limited

Freight and passenger traffic

Moderate

Electric utilities (1900s-present)

Utility debt, project finance

Power purchase agreements, independent power producers

Regulated utility revenues

Very high

Seaports

Public authorities, revenue bonds

Long-term terminal concessions

Shipping fees

High

Airports

Municipal bonds, PPPs

Airline gate leases

Passenger and airline fees

High

Toll roads

Project finance, PPPs

SPVs, concession agreements

Toll revenues

Very high

Mobile networks

Corporate debt, tower leasing

Tower REIT leases

Wireless subscriptions

Very high

Fiber networks

Project finance, infrastructure funds

Long-term IRUs, dark fiber leases

Wholesale and retail access

Extremely high

AI data centers

Corporate debt, project finance, lease finance

Long-term data center leases, PPAs, equipment commitments

Cloud and AI services

Highest


Electricity infrastructure evolved from vertically integrated utilities financing everything on their own balance sheets to today's mixture of:

  • utility-owned assets,

  • independent power producers,

  • project-financed generation,

  • long-term power purchase agreements (PPAs), and

  • infrastructure funds.


The important innovation was separating ownership from usage. A utility could commit to buying electricity for 20–30 years without necessarily owning the generating plant. That resembles today's hyperscalers signing 15- to 30-year leases for AI campuses built by third-party developers.


Modern project finance emerged because infrastructure became too expensive for sponsors to fund entirely on their own balance sheets.

Instead:

  • a special-purpose vehicle (SPV) owns the project,

  • lenders are repaid primarily from project cash flow,

  • the sponsor's liability is limited,

  • long-term customer contracts reduce lender risk.

This structure became common for:

  • toll roads,

  • airports,

  • ports,

  • power plants,

  • pipelines.


AI data centers resemble these projects.


Wireless carriers originally owned virtually everything:

  • towers,

  • land,

  • buildings,

  • backup power.


Beginning around 2000 they sold towers to companies such as American Tower, Crown Castle, and SBA Communications.


Instead of ownership they signed:

  • 10- to 20-year leases,

  • automatic renewals,

  • inflation escalators.


From an economic perspective, tower lease obligations became debt-like commitments while freeing carriers' balance sheets for spectrum purchases and network equipment. Hyperscalers appear to be following almost exactly the same path.


AI Involves Lots of Politicial Choices: For Whom and Why

It’s easy enough to argue that widespread use of artificial intelligence has some potential to raise important new questions about economic ...